Overview

Dataset statistics

Number of variables8
Number of observations124
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory67.1 B

Variable types

Categorical6
Text2

Dataset

Description영월군 지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공하여 물건 유형에 따른 세부담 수준의 형평성 검토 및 부동산 등 관련분야 규제정책 대상 확인 시 기초자료로 활용
Author강원도 영월군
URLhttps://www.data.go.kr/data/15079653/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
세목명 is highly overall correlated with 세원 유형명High correlation
세원 유형명 is highly overall correlated with 세목명High correlation

Reproduction

Analysis started2023-12-12 00:17:32.814226
Analysis finished2023-12-12 00:17:33.319152
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
강원도
124 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도
2nd row강원도
3rd row강원도
4th row강원도
5th row강원도

Common Values

ValueCountFrequency (%)
강원도 124
100.0%

Length

2023-12-12T09:17:33.376592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:33.467937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 124
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영월군
124 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영월군
2nd row영월군
3rd row영월군
4th row영월군
5th row영월군

Common Values

ValueCountFrequency (%)
영월군 124
100.0%

Length

2023-12-12T09:17:33.558149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:33.654322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영월군 124
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
42750
124 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42750
2nd row42750
3rd row42750
4th row42750
5th row42750

Common Values

ValueCountFrequency (%)
42750 124
100.0%

Length

2023-12-12T09:17:33.785833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:33.892833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42750 124
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2018
42 
2017
41 
2019
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2018 42
33.9%
2017 41
33.1%
2019 41
33.1%

Length

2023-12-12T09:17:33.990231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:34.113007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 42
33.9%
2017 41
33.1%
2019 41
33.1%

세목명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
취득세
27 
주민세
27 
자동차세
21 
재산세
15 
지방소득세
12 
Other values (6)
22 

Length

Max length7
Median length3
Mean length3.6935484
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row교육세
2nd row취득세
3rd row취득세
4th row취득세
5th row취득세

Common Values

ValueCountFrequency (%)
취득세 27
21.8%
주민세 27
21.8%
자동차세 21
16.9%
재산세 15
12.1%
지방소득세 12
9.7%
등록면허세 6
 
4.8%
지역자원시설세 6
 
4.8%
교육세 3
 
2.4%
담배소비세 3
 
2.4%
체납 3
 
2.4%

Length

2023-12-12T09:17:34.235425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 27
21.8%
주민세 27
21.8%
자동차세 21
16.9%
재산세 15
12.1%
지방소득세 12
9.7%
등록면허세 6
 
4.8%
지역자원시설세 6
 
4.8%
교육세 3
 
2.4%
담배소비세 3
 
2.4%
체납 3
 
2.4%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
교육세
 
3
토지
 
3
승합
 
3
주택(단독)
 
3
주택(개별)
 
3
Other values (37)
109 

Length

Max length11
Median length8
Mean length6.4516129
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row교육세
2nd row건축물
3rd row주택(단독)
4th row주택(개별)
5th row기타

Common Values

ValueCountFrequency (%)
교육세 3
 
2.4%
토지 3
 
2.4%
승합 3
 
2.4%
주택(단독) 3
 
2.4%
주택(개별) 3
 
2.4%
기타 3
 
2.4%
항공기 3
 
2.4%
기계장비 3
 
2.4%
차량 3
 
2.4%
선박 3
 
2.4%
Other values (32) 94
75.8%

Length

2023-12-12T09:17:34.357308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교육세 3
 
2.4%
주민세(개인균등 3
 
2.4%
체납 3
 
2.4%
주민세(종업원분 3
 
2.4%
주민세(특별징수 3
 
2.4%
주민세(법인세분 3
 
2.4%
주민세(양도소득 3
 
2.4%
주민세(종합소득 3
 
2.4%
주민세(법인균등 3
 
2.4%
주민세(개인사업 3
 
2.4%
Other values (32) 94
75.8%

부과건수
Text

Distinct99
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T09:17:34.593089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.8145161
Min length1

Characters and Unicode

Total characters473
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)76.6%

Sample

1st row100,814
2nd row760
3rd row989
4th row390
5th row11
ValueCountFrequency (%)
21
 
16.9%
12 3
 
2.4%
1 3
 
2.4%
293 2
 
1.6%
388 1
 
0.8%
3,335 1
 
0.8%
216 1
 
0.8%
19 1
 
0.8%
1,212 1
 
0.8%
1,149 1
 
0.8%
Other values (89) 89
71.8%
2023-12-12T09:17:35.271924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 59
12.5%
, 50
10.6%
8 45
9.5%
2 43
9.1%
42
8.9%
9 38
8.0%
3 36
7.6%
0 36
7.6%
6 36
7.6%
5 26
5.5%
Other values (3) 62
13.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
76.1%
Other Punctuation 50
 
10.6%
Space Separator 42
 
8.9%
Dash Punctuation 21
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 59
16.4%
8 45
12.5%
2 43
11.9%
9 38
10.6%
3 36
10.0%
0 36
10.0%
6 36
10.0%
5 26
7.2%
7 22
 
6.1%
4 19
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 473
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 59
12.5%
, 50
10.6%
8 45
9.5%
2 43
9.1%
42
8.9%
9 38
8.0%
3 36
7.6%
0 36
7.6%
6 36
7.6%
5 26
5.5%
Other values (3) 62
13.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 59
12.5%
, 50
10.6%
8 45
9.5%
2 43
9.1%
42
8.9%
9 38
8.0%
3 36
7.6%
0 36
7.6%
6 36
7.6%
5 26
5.5%
Other values (3) 62
13.1%

부과금액
Text

Distinct104
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T09:17:35.563192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.8306452
Min length3

Characters and Unicode

Total characters1219
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)83.1%

Sample

1st row3,491,690,000
2nd row1,971,542,000
3rd row1,119,010,000
4th row820,112,000
5th row26,850,000
ValueCountFrequency (%)
21
 
16.9%
3,491,690,000 1
 
0.8%
605,883,000 1
 
0.8%
2,887,637,000 1
 
0.8%
452,981,000 1
 
0.8%
38,713,000 1
 
0.8%
258,960,000 1
 
0.8%
1,095,167,000 1
 
0.8%
1,194,191,000 1
 
0.8%
3,519,696,000 1
 
0.8%
Other values (94) 94
75.8%
2023-12-12T09:17:35.940717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 368
30.2%
, 239
19.6%
1 75
 
6.2%
2 66
 
5.4%
8 64
 
5.3%
5 63
 
5.2%
4 61
 
5.0%
9 61
 
5.0%
7 56
 
4.6%
6 53
 
4.3%
Other values (3) 113
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 916
75.1%
Other Punctuation 239
 
19.6%
Space Separator 42
 
3.4%
Dash Punctuation 22
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 368
40.2%
1 75
 
8.2%
2 66
 
7.2%
8 64
 
7.0%
5 63
 
6.9%
4 61
 
6.7%
9 61
 
6.7%
7 56
 
6.1%
6 53
 
5.8%
3 49
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 239
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1219
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 368
30.2%
, 239
19.6%
1 75
 
6.2%
2 66
 
5.4%
8 64
 
5.3%
5 63
 
5.2%
4 61
 
5.0%
9 61
 
5.0%
7 56
 
4.6%
6 53
 
4.3%
Other values (3) 113
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1219
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 368
30.2%
, 239
19.6%
1 75
 
6.2%
2 66
 
5.4%
8 64
 
5.3%
5 63
 
5.2%
4 61
 
5.0%
9 61
 
5.0%
7 56
 
4.6%
6 53
 
4.3%
Other values (3) 113
 
9.3%

Correlations

2023-12-12T09:17:36.032130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수
과세년도1.0000.0000.0000.000
세목명0.0001.0001.0000.897
세원 유형명0.0001.0001.0000.951
부과건수0.0000.8970.9511.000
2023-12-12T09:17:36.142770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세원 유형명세목명
과세년도1.0000.0000.000
세원 유형명0.0001.0000.852
세목명0.0000.8521.000
2023-12-12T09:17:36.222598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명
과세년도1.0000.0000.000
세목명0.0001.0000.852
세원 유형명0.0000.8521.000

Missing values

2023-12-12T09:17:33.160094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:17:33.268343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
0강원도영월군427502017교육세교육세100,8143,491,690,000
1강원도영월군427502017취득세건축물7601,971,542,000
2강원도영월군427502017취득세주택(단독)9891,119,010,000
3강원도영월군427502017취득세주택(개별)390820,112,000
4강원도영월군427502017취득세기타1126,850,000
5강원도영월군427502017취득세항공기--
6강원도영월군427502017취득세기계장비215433,033,000
7강원도영월군427502017취득세차량3,1872,613,084,000
8강원도영월군427502017취득세선박--
9강원도영월군427502017취득세토지3,2993,955,485,000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
114강원도영월군427502019지방소득세지방소득세(특별징수)6,8272,227,896,000
115강원도영월군427502019지방소득세지방소득세(법인소득)7212,005,238,000
116강원도영월군427502019지방소득세지방소득세(양도소득)6261,481,476,000
117강원도영월군427502019지방소득세지방소득세(종합소득)3,249826,489,000
118강원도영월군427502019등록면허세등록면허세(면허)8,888155,448,000
119강원도영월군427502019등록면허세등록면허세(등록)9,453670,908,000
120강원도영월군427502019지역자원시설세지역자원시설세(소방)11,882622,968,000
121강원도영월군427502019지역자원시설세지역자원시설세(특자)3661,653,154,000
122강원도영월군427502019담배소비세담배소비세812,924,848,000
123강원도영월군427502019체납체납36,9094,097,056,000